Anirudh Goyal
- Artificial Intelligence top 2%
- Anomaly Detection Techniques and Applications 5
- Neural Networks and Applications 5
- Adversarial Robustness in Machine Learning 4
- Reinforcement Learning in Robotics 4
- Domain Adaptation and Few-Shot Learning 4
- Health Informatics top 10%
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- Video Surveillance and Tracking Methods 3
- Multimodal Machine Learning Applications 3
- Signal Processing top 10%
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- Neural dynamics and brain function 4
- Co-authors
- Yoshua BengioNan Rosemary KeBernhard SchölkopfFrancesco LocatelloStefan BauerNal KalchbrennerAlex LambAaron Courville
- Partner nations
- CanadaUnited StatesIndia
In The Last Decade
Anirudh Goyal
35 papers receiving 862 citations
Hit Papers
Peers
Comparison fields: 5 of 126
- Artificial Intelligence 518
- Health Informatics 18
- Computer Vision and Pattern Recognition 213
- Signal Processing 58
- Management Science and Operations Research 60
Countries citing papers authored by Anirudh Goyal
This map shows the geographic impact of Anirudh Goyal's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Anirudh Goyal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anirudh Goyal more than expected).
Fields of papers citing papers by Anirudh Goyal
This network shows the impact of papers produced by Anirudh Goyal. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Anirudh Goyal. The network helps show where Anirudh Goyal may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Anirudh Goyal, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2023 | 5 | |
| 4 | Toward Causal Representation Learningbreakdown → | 2021 | 519 |
| 5 | 2021 | 8 | |
| 6 | Discrete-Valued Neural Communication in Structured Architectures Enhances Generalization | 2021 | 1 |
| 7 | Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives | 2020 | 2 |
| 8 | Learning the Arrow of Time for Problems in Reinforcement Learning | 2020 | 2 |
| 9 | Untangling tradeoffs between recurrence and self-attention in artificial neural networks | 2020 | 6 |
| 10 | Is Independence all you need? On the Generalization of Representations Learned from Correlated Data | 2020 | 1 |
| 11 | Top-K Training of GANs: Improving Generators by Making Critics Less Critical | 2020 | 1 |
| 12 | Small-GAN: Speeding up GAN Training using Core-Sets | 2020 | 2 |
| 13 | InfoBot: Transfer and Exploration via the Information Bottleneck | 2019 | 8 |
| 14 | State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations | 2019 | 1 |
| 15 | 2019 | 6 | |
| 16 | Modeling the Long Term Future in Model-Based Reinforcement Learning | 2018 | 5 |
| 17 | Extending the Framework of Equilibrium Propagation to General Dynamics | 2018 | 1 |
| 18 | 2018 | 11 | |
| 19 | An Actor-Critic Algorithm for Structured Prediction | 2016 | 1 |
| 20 | 2013 | 2 |
About Anirudh Goyal
Anirudh Goyal is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Software, having authored 38 papers that have together received 901 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (5 papers), Neural Networks and Applications (5 papers), Adversarial Robustness in Machine Learning (4 papers), Reinforcement Learning in Robotics (4 papers), Domain Adaptation and Few-Shot Learning (4 papers), Neural dynamics and brain function (4 papers), Video Surveillance and Tracking Methods (3 papers) and Multimodal Machine Learning Applications (3 papers). The work is most often cited by research in Artificial Intelligence (518 citations), Health Informatics (18 citations) and Computer Vision and Pattern Recognition (213 citations). Anirudh Goyal has collaborated with scholars based in Canada, United States and India. Frequent co-authors include Yoshua Bengio, Nan Rosemary Ke, Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nal Kalchbrenner, Alex Lamb, Aaron Courville, Ying Zhang and Saizheng Zhang. Their work appears in journals such as Cancer Research, Proceedings of the IEEE and BMC Public Health.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.